activation-functions | Topic | Ecosyste.ms: Repos

Topic: "activation-functions"

digantamisra98/Mish

Official Repository for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]

Language: Jupyter Notebook - Size: 185 MB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 1,298 - Forks: 131

lucidrains/siren-pytorch

Pytorch implementation of SIREN - Implicit Neural Representations with Periodic Activation Function

Language: Python - Size: 15.6 KB - Last synced at: 21 days ago - Pushed at: almost 2 years ago - Stars: 487 - Forks: 51

harleyszhang/dl_note

深度学习系统笔记，包含深度学习数学基础知识、神经网络基础部件详解、深度学习炼丹策略、模型压缩算法详解。

Language: Python - Size: 189 MB - Last synced at: 14 days ago - Pushed at: about 1 month ago - Stars: 468 - Forks: 66

KumapowerLIU/Rethinking-Inpainting-MEDFE

Rethinking Image Inpainting via a Mutual Encoder Decoder with Feature Equalizations. ECCV 2020 Oral

Language: Python - Size: 2.94 MB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 361 - Forks: 51

dalmia/siren

PyTorch implementation of Sinusodial Representation networks (SIREN)

Language: Python - Size: 6.97 MB - Last synced at: 19 days ago - Pushed at: over 2 years ago - Stars: 264 - Forks: 11

Niranjankumar-c/DeepLearning-PadhAI

All the code files related to the deep learning course from PadhAI

Language: Jupyter Notebook - Size: 3.61 MB - Last synced at: over 1 year ago - Pushed at: about 5 years ago - Stars: 90 - Forks: 121

densechen/AReLU

AReLU: Attention-based-Rectified-Linear-Unit

Language: Jupyter Notebook - Size: 8.99 MB - Last synced at: 7 months ago - Pushed at: almost 4 years ago - Stars: 61 - Forks: 8

Wongi-Choi1014/Korean-OCR-Model-Design-based-on-Keras-CNN

Korean OCR Model Design(한글 OCR 모델 설계)

Language: Python - Size: 33.3 MB - Last synced at: over 1 year ago - Pushed at: almost 5 years ago - Stars: 58 - Forks: 22

scart97/Siren-fastai2

Unofficial implementation of 'Implicit Neural Representations with Periodic Activation Functions'

Language: Jupyter Notebook - Size: 5.42 MB - Last synced at: 2 months ago - Pushed at: almost 5 years ago - Stars: 51 - Forks: 4

M-68/ActivationFunctions

Implementing activation functions from scratch in Tensorflow.

Language: Jupyter Notebook - Size: 202 KB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 36 - Forks: 4

AKASH2907/Introduction_to_Deep_Learning_Coursera

Intro to Deep Learning by National Research University Higher School of Economics

Language: Jupyter Notebook - Size: 13.3 MB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 36 - Forks: 31

soumik12345/Pix2Pix

Image to Image Translation using Conditional GANs (Pix2Pix) implemented using Tensorflow 2.0

Language: Jupyter Notebook - Size: 78 MB - Last synced at: about 1 month ago - Pushed at: over 5 years ago - Stars: 29 - Forks: 1

pouyaardehkhani/ActTensor

ActTensor: Activation Functions for TensorFlow. https://pypi.org/project/ActTensor-tf/ Authors: Pouya Ardehkhani, Pegah Ardehkhani

Language: Python - Size: 1.96 MB - Last synced at: 2 months ago - Pushed at: about 1 year ago - Stars: 26 - Forks: 4

poopingface/sigmoidcolon

:poop: Sigmoid Colon: The biologically inspired activation function.

Language: Python - Size: 211 KB - Last synced at: 21 days ago - Pushed at: over 2 years ago - Stars: 25 - Forks: 1

epishchik/TrainableActivation

Implementation for the article "Trainable Activations for Image Classification"

Language: Python - Size: 1.54 MB - Last synced at: 2 months ago - Pushed at: over 1 year ago - Stars: 24 - Forks: 2

okozelsk/NET 📦

Reservoir computing library for .NET. Enables ESN , LSM and hybrid RNNs using analog and spiking neurons working together.

Language: C# - Size: 18.7 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 22 - Forks: 6

XAheli/Predicting-Indian-Stocks-Price-with-Stacked-LSTM

Predicting Indian stock prices using Stacked LSTM model. Analysing Reliance, Tata Steel, HDFC Bank, Infosys data. Data prep, EDA, hyperparameter tuning.

Language: Jupyter Notebook - Size: 1.61 MB - Last synced at: 2 months ago - Pushed at: over 1 year ago - Stars: 21 - Forks: 6

Rishit-dagli/GLU

An easy-to-use library for GLU (Gated Linear Units) and GLU variants in TensorFlow.

Language: Python - Size: 220 KB - Last synced at: 12 days ago - Pushed at: over 2 years ago - Stars: 20 - Forks: 4

ChristophReich1996/SmeLU

PyTorch reimplementation of the Smooth ReLU activation function proposed in the paper "Real World Large Scale Recommendation Systems Reproducibility and Smooth Activations" [arXiv 2022].

Language: Python - Size: 68.4 KB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 20 - Forks: 2

Ameobea/rnn-viz

Interactive visualizations and demos that are used in a blog post I wrote about logic in the context of neural networks

Language: Jupyter Notebook - Size: 1.82 MB - Last synced at: 2 months ago - Pushed at: 8 months ago - Stars: 17 - Forks: 1

ThomasMrY/ActivationFunctionDemo

[TCAD 2018] Code for “Design Space Exploration of Neural Network Activation Function Circuits”

Language: Python - Size: 2.37 MB - Last synced at: over 2 years ago - Pushed at: over 6 years ago - Stars: 17 - Forks: 5

MrGoriay/pwlu-pytorch

Unofficial pytorch implementation of Piecewise Linear Unit dynamic activation function

Language: Python - Size: 10.7 KB - Last synced at: 10 months ago - Pushed at: over 2 years ago - Stars: 16 - Forks: 2

luca-parisi/quantum_relu

QReLU and m-QReLU: Two novel quantum activation functions for Deep Learning in TensorFlow, Keras, and PyTorch

Language: Python - Size: 43.9 KB - Last synced at: about 1 month ago - Pushed at: 9 months ago - Stars: 14 - Forks: 7

AaltoML/PeriodicBNN

Code for 'Periodic Activation Functions Induce Stationarity' (NeurIPS 2021)

Language: Jupyter Notebook - Size: 4.86 MB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 14 - Forks: 2

lucylow/salty-wet-man

Binary classification to filter and block unsolicited NSFW content from annoying coworkers... --- ...

Language: JavaScript - Size: 6.09 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 13 - Forks: 3

shuuchen/frelu.pytorch

A PyTorch implementation of funnel activation https://arxiv.org/pdf/2007.11824.pdf

Language: Python - Size: 186 KB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 13 - Forks: 3

kumar-shridhar/ProbAct-Probabilistic-Activation-Function

Official PyTorch implementation of the paper : ProbAct: A Probabilistic Activation Function for Deep Neural Networks.

Language: Jupyter Notebook - Size: 1.09 MB - Last synced at: 2 months ago - Pushed at: about 6 years ago - Stars: 13 - Forks: 4

MainakRepositor/Activation-Infopedia

Language: Python - Size: 146 KB - Last synced at: about 1 month ago - Pushed at: over 1 year ago - Stars: 8 - Forks: 1

mohamedamine99/Visualizing-what-convnets-learn

This Github repository explains the impact of different activation functions on CNN's performance and provides visualizations of activations, convnet filters, and heatmaps of class activation for easier understanding of how CNN works.

Language: Jupyter Notebook - Size: 630 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 6 - Forks: 0

MoinDalvs/Neural_Networks_From_Scratch

Neural_Networks_From_Scratch

Language: Jupyter Notebook - Size: 1.56 MB - Last synced at: 2 months ago - Pushed at: almost 3 years ago - Stars: 6 - Forks: 4

kmario23/activation-functions-3D-viz

3D visualization of common activation functions

Language: Python - Size: 2.94 MB - Last synced at: 2 months ago - Pushed at: over 4 years ago - Stars: 6 - Forks: 3

pkonowrocki/Neural-network

Multilayer neural network framework implementation, used for classification and regression task. Can use multiple activation functions with backpropagation based on autograd library. Contains polynomial activation function for regression task.

Language: Python - Size: 58.6 KB - Last synced at: almost 2 years ago - Pushed at: over 5 years ago - Stars: 6 - Forks: 1

TechBison/NN-assignment-1

Language: Jupyter Notebook - Size: 470 KB - Last synced at: about 2 months ago - Pushed at: over 6 years ago - Stars: 6 - Forks: 0

MoinDalvs/Neural_Network_Regression_Gas_Turbines

Predicting Turbine Energy Yield (TEY) using ambient variables as features.

Language: Jupyter Notebook - Size: 2.53 MB - Last synced at: about 2 months ago - Pushed at: almost 3 years ago - Stars: 5 - Forks: 1

ChristophReich1996/Pade-Activation-Unit

PyTorch reimplementation of the paper "Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks" [ICLR 2020].

Language: Python - Size: 19.5 KB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 5 - Forks: 1

RahulBhalley/deep-learning-with-swift-for-tensorflow-book

Official source code for "Deep Learning with Swift for TensorFlow" 📖

Language: Swift - Size: 716 KB - Last synced at: 2 months ago - Pushed at: about 4 years ago - Stars: 5 - Forks: 0

luca-parisi/m_arcsinh

m-arcsinh: A Reliable and Efficient Function for Supervised Machine Learning (scikit-learn, TensorFlow, and Keras) and Feature Extraction (scikit-learn)

Language: Python - Size: 52.7 KB - Last synced at: 2 months ago - Pushed at: 9 months ago - Stars: 4 - Forks: 1

vishal815/Customer-Churn-Prediction-using-Artificial-Neural-Network

This project involves building an Artificial Neural Network (ANN) for predicting customer churn. The dataset used contains various customer attributes, and the ANN is trained to predict whether a customer is likely to leave the bank.

Language: Jupyter Notebook - Size: 313 KB - Last synced at: 2 months ago - Pushed at: over 1 year ago - Stars: 4 - Forks: 1

AFAgarap/vanishing-gradients

Avoiding the vanishing gradients problem by adding random noise and batch normalization

Language: Python - Size: 175 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 4 - Forks: 1

ChristophReich1996/SmeLU-Triton

Triton reimplementation of the Smooth ReLU activation function proposed in the paper "Real World Large Scale Recommendation Systems Reproducibility and Smooth Activations" [arXiv 2022].

Language: Python - Size: 69.3 KB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 4 - Forks: 0

tahmid0007/Low_Pass_ReLU

Corruption Robust Image Classification with a new Activation Function. Our proposed Activation Function is inspired by the Human Visual System and a classic signal processing fix for data corruption.

Language: MATLAB - Size: 2.34 MB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 4 - Forks: 1

luca-parisi/hyper_sinh

hyper-sinh: An Accurate and Reliable Activation Function from Shallow to Deep Learning in TensorFlow, Keras, and PyTorch

Language: Python - Size: 36.1 KB - Last synced at: 2 months ago - Pushed at: 9 months ago - Stars: 3 - Forks: 2

kaintels/torchact

TorchAct, collection of activation function for PyTorch. https://pypi.org/project/torchact/

Language: Python - Size: 71.3 KB - Last synced at: 15 days ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 0

seymayucer/siren-tf2

Unofficial SIRENs implementation using Tensorflow 2.

Language: Python - Size: 8.5 MB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 3 - Forks: 0

bhattbhavesh91/activiation-functions

Simple Tutorial to Explain the Pros and Cons of Sigmoid Activation Function

Language: Jupyter Notebook - Size: 52.7 KB - Last synced at: about 2 months ago - Pushed at: about 4 years ago - Stars: 3 - Forks: 5

dbrcina/BSc-Thesis-FER-2019-20

BSc Thesis at FER-2019/20 led by doc. dr. sc. Marko Čupić

Language: TeX - Size: 12.2 MB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 3 - Forks: 0

mainkoon81/Study-09-MachineLearning-C

**DeepLearning** Intro.. Need to wrap up more projects here...

Language: Jupyter Notebook - Size: 188 KB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 3 - Forks: 6

swalpa/LiSHT

This is a Keras implementation of the paper "LiSHT: Non-Parametric Linearly Scaled Hyperbolic Tangent Activation Function for Neural Networks" - https://arxiv.org/abs/1901.05894

Size: 696 KB - Last synced at: over 2 years ago - Pushed at: over 6 years ago - Stars: 3 - Forks: 3

shaheennabi/Deep-Learning-Practices-and-Mini-Projects

Welcome to Deep Learning & Math with Python! 🚀💥 Here, we blend code and theory to build deep learning algorithms from scratch and explore the math behind them. 🧠⚡ Whether you're just starting or a seasoned pro, this space is all about learning, experimenting, and creating AI magic together! 🔥🎆 Let's code, learn, and innovate!

Language: Jupyter Notebook - Size: 427 KB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 2 - Forks: 0

NikolasMarkou/dl_techniques

Advanced deep learning learning techniques, layers, activations loss functions, all in keras / tensorflow

Language: Python - Size: 1.33 MB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 2 - Forks: 0

RajK01/Google-Customer-Revenue-Prediction

The main aim of this project is to built a predictive model using G Store data to predict the TOTAL REVENUE per customer that helps in better use of marketing budget.

Language: Jupyter Notebook - Size: 5.53 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 2 - Forks: 0

rothflyingjoe/Discord-Nitro-Activator

Size: 1.95 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 0

himanshuvnm/Generalized-Gaussian-Radial-Basis-Function-in-Artificial-Intelligence-MATLAB

This is the recent work of my on the importance and application of mathematical function around its Hilbert function theory on artificial intelligence algorithms. The main motivation was the desire of improving the convergence rate and learning rate of various learning algorithms via Generalized Gaussian Radial Basis Function.

Language: MATLAB - Size: 10.8 MB - Last synced at: about 1 month ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

NonlinearArtificialIntelligenceLab/jaxDiversity

Jax implementation of metalearning diversity paper

Language: Jupyter Notebook - Size: 1.74 MB - Last synced at: 6 months ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 0

MEGARAJAN-S/ARTIFICIALNEURALNETWORK

This project is about building a artificial neural network using pytorch library. I am sharing the code and output for my project.

Language: Python - Size: 7.81 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 0

Siddhipatade/Activation-function

Activation Function

Language: Jupyter Notebook - Size: 118 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 1

TruongNhanNguyen/Implement-a-Feed-Forward-Neural-Network-from-Scratch-with-Numpy

A simple and easy-to-use feed forward neural network implemented from scratch using Numpy. Includes activation functions, loss functions, and optimizers.

Language: Python - Size: 9.77 KB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

arbiter1elegantiae/Robustness-of-deep-neural-networks-with-trainable-activation-functions

Robustness of Deep Neural Networks using Trainable Activation Functions

Language: Jupyter Notebook - Size: 179 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

ada-k/DeepLearningArchitectures

Implementations of various deep learning architectures + extra theoretical information

Language: Python - Size: 57.6 KB - Last synced at: over 2 years ago - Pushed at: almost 3 years ago - Stars: 2 - Forks: 0

Azeemaj101/Deep-Learning-Math-Concepts

Language: Jupyter Notebook - Size: 286 MB - Last synced at: over 2 years ago - Pushed at: almost 3 years ago - Stars: 2 - Forks: 0

ChaitanyaC22/Neural-Network-using-Numpy

Introduction to Neural Networks (Create a neural network using Numpy)

Language: Jupyter Notebook - Size: 15.8 MB - Last synced at: 3 months ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 0

bhattbhavesh91/why-is-relu-non-linear

A small walk-through to show why ReLU is non linear!

Language: Jupyter Notebook - Size: 119 KB - Last synced at: about 2 months ago - Pushed at: about 4 years ago - Stars: 2 - Forks: 5

kalthommusa/Udacity-Intro-to-Deep-Learning-Introduction-to-Neural-Network

Collection of my notes from Udacity's Intro to Deep Learning--> Introduction to Neural Networks course.

Size: 8.65 MB - Last synced at: 3 months ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 0

xyproto/af

:zap: Activation functions for neural networks

Language: Go - Size: 29.3 KB - Last synced at: about 1 month ago - Pushed at: over 5 years ago - Stars: 2 - Forks: 1

kplachkov/Deep-Learning

Essential deep learning algorithms, concepts, examples and visualizations with TensorFlow. Popular and custom neural network architectures. Applications of neural networks.

Language: Jupyter Notebook - Size: 55.5 MB - Last synced at: over 2 years ago - Pushed at: over 6 years ago - Stars: 2 - Forks: 3

ecotner/ConvexityAnnealing

Graduated optimization on neural networks via adjustment of activation functions

Language: Python - Size: 23.4 KB - Last synced at: over 2 years ago - Pushed at: over 6 years ago - Stars: 2 - Forks: 1

ashioyajotham/exploring_saes

Implementation and analysis of Sparse Autoencoders for neural network interpretability research. Features interactive visualization dashboard and W&B integration.

Language: Python - Size: 59.7 MB - Last synced at: 27 days ago - Pushed at: 27 days ago - Stars: 1 - Forks: 2

qiyaozheng/Backpropagation-DEMO

A demonstration of backpropagation using a simple neural network to understand how different activation functions and network structures impact learning various data patterns. Includes experiments with Sigmoid, Tanh, and ReLU on eight unique patterns.

Language: Jupyter Notebook - Size: 444 KB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

PujanMotiwala/the_fun_activations

Supercharge your neural network models with our top-tier activation functions repository. Ideal for data scientists and ML enthusiasts, featuring comprehensive guides, practical implementations, and detailed comparisons. Dive into advanced AI techniques and make impactful contributions today!

Language: Python - Size: 979 KB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 1 - Forks: 0

hediyeorhan/LogisticRegressionWithArduino

Language: C - Size: 4.09 MB - Last synced at: 3 months ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

jElhamm/Activation-Functions

"The 'Activation Functions' project repository contains implementations of various activation functions commonly used in neural networks. "

Language: Python - Size: 2.06 MB - Last synced at: 2 months ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

Priyanshux085/LeviLayer

This project provides an interactive dashboard for analyzing the different activation function in neural networks. LeviLayer is a novel activation function that has shown promising results in various deep learning tasks. With this dashboard, users can explore the behavior of LeviLayer and compare it with other popular activation functions.

Language: Python - Size: 2.93 KB - Last synced at: 8 months ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

Kushashu-1/Activation_function

It is small Web app for Visualization of Activation Function

Language: Python - Size: 21.5 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

sef007/Neural-Network-Email-Classifier-Numpy-Only

Neural Network using NumPy, V1: Built from scratch. V2: Optimised with hyperparameter search.

Language: Python - Size: 780 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

sef007/NN-Numpy-Only-HOG-Feature-Extraction-and-ML-Library-Integration

Digit Recognition Neural Network: Built from scratch using only NumPy. Optimised version includes HOG feature extraction. Third version utilises prebuilt ML libraries.

Language: Python - Size: 10.4 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

vtramo/neural-networks-experiments-from-scratch

The objective of this repository is to provide a learning and experimentation environment to better understand the details and fundamental concepts of neural networks by building neural networks from scratch.

Language: Python - Size: 12.2 MB - Last synced at: 14 days ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

JLeigh101/deep-learning-challenge

NU Bootcamp Module 21

Language: Jupyter Notebook - Size: 27.3 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

umarwaseeem/Activation-Func-Visualizer

Visualize Neural Network activation functions with a python manim library script

Language: Python - Size: 759 KB - Last synced at: 11 months ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

padobrik/kidney-pathology-classification

Experimenting with the quality of classification of the kidney pathology in case of different activation functions

Language: Jupyter Notebook - Size: 995 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

DalhousieAI/pytorch-logit-logic

Logit-space logical activation functions for pytorch

Language: Python - Size: 1.63 MB - Last synced at: 10 months ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

SameetAsadullah/Neural-Network-Implementation

Neural Network implemented with different Activation Functions i.e, sigmoid, relu, leaky-relu, softmax and different Optimizers i.e, Gradient Descent, AdaGrad, RMSProp, Adam. You can choose different loss functions as well i.e, cross-entropy loss, hinge-loss, mean squared error (MSE)

Language: Jupyter Notebook - Size: 5.86 KB - Last synced at: 14 days ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0

maideas/numpy-neural-network

A NumPy based Neural Network Package Implementation

Language: Python - Size: 91.3 MB - Last synced at: over 2 years ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0

MrAsimZahid/Neural-Networks-from-Scratch

Building Neural Networks from Scratch in raw Python

Language: Jupyter Notebook - Size: 5.86 KB - Last synced at: over 2 years ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0

ShotaDeguchi/dnn_activation

investigates the relationship between DNN approximation and activation function.

Language: Python - Size: 3.62 MB - Last synced at: over 2 years ago - Pushed at: about 3 years ago - Stars: 1 - Forks: 0

yester31/DL_Layer

Making a Deep Learning Framework with C++

Language: C++ - Size: 35.6 MB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 1

JohnLins/NNActivationExperiment

My science fair experiment for the CCC science far (2nd place). "How various activation functions affect the loss and output of a neural network"

Language: Python - Size: 32.8 MB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 1 - Forks: 0

gchacaltana/py_artificial_neuron

Neurona artificial

Language: Python - Size: 9.77 KB - Last synced at: about 1 year ago - Pushed at: about 4 years ago - Stars: 1 - Forks: 0

KienMN/Activation-Experiments

Experiments using different activation functions.

Language: Python - Size: 34.2 KB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 1

alorber/Quadratic-Activation-Functions

Deep Learning Final Project

Language: Jupyter Notebook - Size: 1.39 MB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

crosstherubicon/Backprop_Hyper-parameters

Understanding hyperparameters of neural network architectures using 3 cost functions, 3 activation functions, 2 regularizations and dropout.

Language: Jupyter Notebook - Size: 1.63 MB - Last synced at: almost 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 1

sakshikakde/CS231n

My solutions for the CS231n (Convolutional Neural Networks for Visual Recognition) assignments.

Language: Jupyter Notebook - Size: 175 MB - Last synced at: almost 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 2

Jitensid/Numras

Language: Jupyter Notebook - Size: 104 KB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

pradeepdev-1995/Gradient-descent

Gradient descent is a first-order iterative optimization algorithm for finding a local minimum of a differentiable function. To find a local minimum of a function using gradient descent, we take steps proportional to the negative of the gradient (or approximate gradient) of the function at the current point. But if we instead take steps proportional to the positive of the gradient, we approach a local maximum of that function; the procedure is then known as gradient ascent.

Language: Jupyter Notebook - Size: 142 KB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0